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Theme: The Future of Engineering Education

Clean the beach, protect the blue: A student-led model for turning environmental awareness into community action [IEEE Student Activities]

October 12, 2026 by Wassim Zili

At 5 p.m. on 11 July 2026, Qaraiya Beach in Monastir, Tunisia, was still full of life. Families were settling near the water, children were playing in the sand, and swimmers were enjoying the final hours of the afternoon. In the middle of this familiar summer scene, a group of young volunteers began preparing an environmental awareness stand, distributing gloves and litter … [Read more...] about Clean the beach, protect the blue: A student-led model for turning environmental awareness into community action [IEEE Student Activities]

Prepare for the job that does not exist yet [The Way Ahead]

October 12, 2026 by Thiago Alencar

When people think of Ecuador, they think of football, tourism, and bananas, rarely of the passionate people who, despite limited opportunities, are quietly rewriting their own stories. This is one of those stories. It’s mine. For more about this article see link below. https://ieeexplore.ieee.org/document/11690793 For the open access PDF link of this article please … [Read more...] about Prepare for the job that does not exist yet [The Way Ahead]

One workshop, one conversation, one symposium: How volunteering opened the world [Techtravel]

October 12, 2026 by Marco Alfonso Vinueza Bustamante

When people think of Ecuador, they think of football, tourism, and bananas, rarely of the passionate people who, despite limited opportunities, are quietly rewriting their own stories. This is one of those stories. It’s mine. For more about this article see link below. https://ieeexplore.ieee.org/document/11690794 For the open access PDF link of this article please … [Read more...] about One workshop, one conversation, one symposium: How volunteering opened the world [Techtravel]

Do you consider yourself an eternal learner? [Student Editorial]

October 12, 2026 by Moira Prates, Matheus Pereira Gomes

It’s good to think that we are in a constant process of expanding the boundaries of what we yet do not know. With every new subject we study, we become aware of a hundred new areas of knowledge that we still need to learn about and explore in greater depth. Perhaps this way of thinking is nothing more than a refuge that helps to cope with the vast amount of information that … [Read more...] about Do you consider yourself an eternal learner? [Student Editorial]

Self-correcting agent: Recovering from danger [Beyond the Degree]

October 12, 2026 by Sheng-Yu Cheng, Wen-Ai Ho, Aaron Wu, Sheng-Hsun Chang

As artificial intelligence (AI) moves off our screens into the physical world, the behavior of autonomous agents is no longer an abstract computation but an action with real consequences. Robots today navigate warehouses, assist in hospitals, and explore unpredictable outdoor environments, yet even minor mistakes can escalate into costly failures. Traditional learning systems, … [Read more...] about Self-correcting agent: Recovering from danger [Beyond the Degree]

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About the Magazine

IEEE Potentials Magazine is the publication dedicated to undergraduate and graduate students and young professionals. IEEE Potentials explores career strategies, the latest in research, and important technical developments. Through its articles, it also relates theories to practical applications, highlights technology’s global impact, and generates international forums that foster the sharing of diverse ideas about the profession.

POPULAR ARTICLE

Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

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